Download Intermodulation Effects Analysis using Complex Bandpass Filterbanks The objective of this paper is to show the ability of complex bandpass filterbanks to extract the intermodulation information that appears when two audio signals interact inside the same analysis band. To perform the analysis a sinusoidal model of the signals has been assumed. Three kinds of signals have been analyzed: a sum of two cosines, a sum of two linear chirps and a sum of two exponential chirps. The complex bandpass filtering of the signals is carried out using a new algorithm based on the Complex Continuous Wavelet Transform. The developed algorithm has been validated comparing the practical results with the theoretical instantaneous amplitude and instantaneous phase of the obtained model of the signals. With the appropriate width, the complex bandpass filters show the same behaviour as our perceptual ability to discriminate interacting tones when they fall inside a critical band of the human ear.
Download Blind Separation of Monaural Signals using Complex Wavelets In this paper, a new method of blind source separation of monaural signals is presented. It is based on similarity criteria between envelopes and frequency trajectories of the components of the signal, and on its onset and offset times. The main difference with previous works is that in this paper, the input signal has been filtered using a flexible complex band pass filter bank that is a discrete version of the Complex Continuous Wavelet Transform (CCWT). Our main purpose is to show that the CCWT can be a powerful tool in blind separation, due to its strong coherence in both time and frequency domains. The presented separation algorithm is a first approximation to this important task. An example set of four synthetically mixed monaural signals have been analyzed by this method. The obtained results are promising.